DocumentCode :
658088
Title :
Sensor and actuator fault detection and isolation based on artificial neural networks and fuzzy logic applicated on induction motor
Author :
Adouni, Amel ; Ben Hamed, Mouna ; Flah, Aymen ; Sbita, Lassaad
Author_Institution :
Electr. Dept., Nat. Eng. Sch. of Gabes, Gabes, Tunisia
fYear :
2013
fDate :
6-8 May 2013
Firstpage :
917
Lastpage :
922
Abstract :
This paper presents a scheme for fault detection and isolation (FDI). It deals with sensors and actuator fault of an induction machine. This scheme is established with artificial intelligent techniques in order to resolve two big troubles. The first is the detection problem. It is resolved with the neural network and the second is the isolation difficulty, it solved using the fuzzy logic. The proposed FDI approach is implemented on Matlab/Simulink software and tested under three types of fault (current, speed sensor fault and inverter fault). The obtained results improving the importance of this method. Then, the actuator and sensor fault are detected and isolated successfully.
Keywords :
fault diagnosis; fuzzy logic; induction motors; neural nets; sensors; Matlab/Simulink software; actuator fault detection; artificial intelligent techniques; artificial neural networks; fault isolation; fuzzy logic; induction machine; induction motor; sensor fault; Actuators; Analytical models; Circuit faults; Fuzzy logic; Induction motors; Inverters; Neural networks;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Control, Decision and Information Technologies (CoDIT), 2013 International Conference on
Conference_Location :
Hammamet
Print_ISBN :
978-1-4673-5547-6
Type :
conf
DOI :
10.1109/CoDIT.2013.6689665
Filename :
6689665
Link To Document :
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